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A visual memory (VM) is a topological map in which a set of key images organized in form of a graph represents an environment. In this paper, a navigation strategy for humanoid robots addressing the problems of localization, visual path planning and path following based on a VM is proposed. Assuming that the VM is given, the main contributions of the paper are: 1) A novel pure vision-based localization...
In this paper, we propose an approach of following a visual path for humanoid navigation. The problem consists in computing appropriate robot velocities for the humanoid walking task from the visual data shared between the current robot view and a set of target images. Two types of visual controllers are evaluated: a position-based scheme and an image-based scheme. Both of them rely on the estimation...
This paper proposes a novel approach for the simultaneous localization and reconstruction of a 3D object. This reconstruction is done with a small humanoid platform by the only means of monocular vision.We combine (1) a stochastic control approach to decide how to move the robot such that the object can be both localized with respect to the robot and correctly reconstructed, and (2) a space carving...
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